Projection systems are widely used in training, sales, and business environments. FIG. 1 shows one example of a projection system 100 that includes a projector 102 positioned on a horizontal surface 104. The surface 104 is typically a desk or tabletop. An elevator 120 protrudes from the bottom sides of the projector 102 creating an angle 110 between the surface 104 and the projector 102. Although only one elevator 120 is shown in FIG. 1 one of skill in the art should understand that a plurality of elevators 120 might be employed in the system 100. Likewise, a one of skill in the art should recognize that the projector 102 refers to any system capable of projecting any of a variety of still or moving images (e.g., projection televisions, multimedia projectors, and computer displays).
The angle 110 varies depending on the position of the elevator 120. The elevator 120 tilts the projector 102's position relative to the surface 104 such that projected image 118 moves up or down on a projection surface 114, increasing or decreasing the angle 110. The projection surface 114 might be a wall, screen, or any other surface capable of displaying a projected image 118.
In the example, the projector 102 manipulates image signals 108 that it receives from a computer 106. One of skill in the art should recognize that the projector 102 might receive different types of image signals (e.g., digital or analog signals) from the computer 106. The image signals 108 represent still, partial, or full motion images of the type rendered by the computer 106.
The projector 102 casts the image signals 108 onto the projection surface 114. The resulting projected image 118 centers about a projection axis 116. An angle 112 exists between the projection axis 116 and the projection surface 114. The angle 112 changes responsive to changes in the angle 110.
The projected image 118 is generally undistorted when the projection axis 116 is substantially perpendicular to the projection surface 114 (i.e., the angle 112 is 90 degrees). The projected image 118 typically distorts, however, when the projection axis 116 is not perpendicular to the projection surface 114. This optical distortion is known as keystone distortion because the image resulting from the misalignment appears more trapezoidal than square. For example, the jagged lined image 122 appears wider at the top than at the bottom. Such a distorted image is a distraction that most presenters would prefer to avoid.
Keystone correction typically adjusts for keystone distortion by adding a special, selectable algorithm to the scaling, thereby allowing the image to be altered before it reaches the projection lens. The result is a projected image that is properly squared, even if it is projected at an angle. This allows presenters more flexibility when setting up their projector in variable environments, for example. Keystone correction has two main types: vertical keystone correction and horizontal keystone correction. In the case of CRT projectors, keystone correction is typically provided by changing signals to the horizontal and vertical deflection circuits.
One way to correct optical distortion such as keystone distortion is to perform an image warping operation. Traditionally, image warping is performed by using either a forward address mapping approach or a reverse address mapping approach. In a typical forward address mapping approach, each pixel in a source image is mapped to an appropriate place in the destination image. The reverse address mapping approach involves going through each pixel in the destination image and sampling an appropriate source image pixel.
Forward address mapping approaches are generally more desirable than reverse address mapping approaches because the memory bandwidth requirements only increase when zooming a portion of the image, whereas reverse address mapping approaches typically require increased memory bandwidth when shrinking the image. Since keystoning and warping applications typically require shrinking the majority of the image, a forward address mapping approach would be preferable over a reverse address mapping approach from a cost standpoint. However, existing forward address mapping approaches have at least one undesirable drawback: significant difficulty in ensuring that new information is generated for all of the output pixels.
Another limitation of previous approaches is that the mapping algorithms are usually based on interpolation and interpolation does not address two image quality concerns with correcting optical distortion with fixed pixel imagers: illumination uniformity and variable anti-alias filtering requirements.
Accordingly, a need remains for improved keystone and optical distortion correction.